RuoliuYang/textlatent_zebra_thinkmorph_armAB

Text-Latent (Arm A) vs All-Latent (Arm B) — Zebra-CoT + ThinkMorph 35638 samples/arm, 18 categories. Schema = ULVR/williamium style (sample_id, category, source_dataset, question, answer, input_image, intermediate_image_N, num_intermediate_steps, messages_json). armA_text_latent: real decoded text CoT + latent visual blocks (intermediate_image_1..3). armB_render_latent: reasoning text RENDERED to images, all-latent baseline (intermediate_image_1..17). messages_json = full Monet… See the full description on the dataset page: https://huggingface.co/datasets/RuoliuYang/textlatent_zebra_thinkmorph

<iframe src="https://silytics.si/embed/item/c0feb452-95c0-4143-9761-485c2dd08651" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.